Principal Applied Scientist AI & Robotics

Job Description

Our AI Research team is building end-to-end robot policies that enable dexterous manipulation in real-world environments. We are advancing embodied AI by integrating multimodal perception robot learning architectures and physical execution systems to solve manipulation autonomy and simulation challenges at an industrial scale.

As a Principal Applied Scientist y ou will define technical direction create breakthrough robot learning methodologies and drive the execution of large-scale initiatives that deliver end-to-end manipulation policies. You will architect new model families lead cross-functional research efforts and guide teams in transitioning scientific advances into reliable robotic capabilities deployed in real systems.

What Youll Do

Define the research strategy and technical roadmap for embodied manipulation policies that span perception training control and deployment.

Invent or advance robot learning architectures (e.g. diffusion-based policies ACT-style agents multimodal embodied transformers) to enable robust dexterous manipulation.

Architect end-to-end policy systems from multimodal sensing to hardware control across simulation and real environments.

Establish standards for data generation demonstrations simulation fidelity evaluation and sim-to-real adaptation for manipulation tasks.

Guide cross-functional efforts to scale robot learning from prototypes to production including reliability constraints observability and performance guarantees.

Mentor scientists and engineers influence hiring and shape research priorities within the organization.

Represent GM in external communities (e.g. CoRL RSS ICRA NeurIPS ) pursue collaborations and drive thought leadership in embodied AI.

Required Qualifications

PhD in a relevant STEM field with a recognized track record in robotics robot learning or embodied AI.

Significant experience designing and deploying robot learning systems on physical hardware including manipulation tasks and real-time policy execution.

Expertise in modern AI architectures (Transformers diffusion models VLM / VLA agents imitation learning offline RL) and ability to extend them to new embodied scenarios.

Mastery of PyTorch including model internals performance optimization distributed training and debugging complex failures.

Hands-on experience with ROS / ROS2 motion planning stacks and integration of ML components into robotic platforms.

Evidence of high-impact contributions : top-tier publications influential open-source efforts field deployments or foundational algorithms.

Proven ability to lead ambiguous multi-disciplinary research programs and deliver tangible embodied AI outcomes.

Preferred Qualifications

Experience establishing research agendas in robot learning or dexterous manipulation that resulted in widely adopted systems or protocols .

Leadership of projects involving perception policy control integration staged training or multi-robot deployment.

Deep expertise in at least one advanced area :

Dexterous manipulation / affordance-driven action

Multi-step task sequencing / long horizon reasoning

Offline RL or imitation learning at scale

Physics-informed or tactile-informed policies

Foundation models for embodied agents

Strong industry or academic presence : invited talks program committees major open-source contributions or collaborations with robotics research institutions.

Why Join Us

You will shape how robots behave in the physical worlddesigning the foundational learning systems that enable dexterous autonomous manipulation across GMs future robotics platforms.

Location : This role is categorized as hybrid. This means the successful candidate is expected to report to the MTV office three times per week or any other frequency dictated by the business.

Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York Colorado California or Washington.

The salary range for this role is 259000 to 320000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

Bonus Potential : An incentive pay program offers payouts based on company performance job level and individual performance.

Benefits : GM offers a variety of health and wellbeing benefit programs. Benefit options include medical dental vision Health Savings Account Flexible Spending Accounts retirement savings plan sickness and accident benefits life insurance paid vacation & holidays tuition assistance programs employee assistance program GM vehicle discounts and more.

Company Vehicle : Upon successful completion of a motor vehicle report review you will be eligible to participate in a company vehicle evaluation program through which you will be assigned a General Motors vehicle to drive and evaluate.

Note : program participants are required to purchase / lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

Relocation : This job may be eligible for relocation benefits.

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About GM

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Benefits Overview

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Required Experience :

Staff IC

Key Skills

Machine Learning,Python,Data Science,AI,R,Research Experience,Sensors,Drug Discovery,Research & Development,Natural Language Processing,Data Analysis Skills,Toxicology Experience

Employment Type : Full-Time

Experience : years

Vacancy : 1